Senior Machine Learning Engineer
Costa Mesa, CAFull-timePosted 5mo agoStill listed today
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At a glance
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Job overview
Kinetic Automation is hiring a Senior Machine Learning Engineer. Kinetic Automation is building a network of automated repair centers for modern vehicles, transitioning the auto industry from mechanically complex vehicles to software-driven ones. The company aims to be the primary infrastructure-as-a-service for servicing future vehicles with robotic repair centers, powered by proprietary software and AI. They are a venture-backed startup with a clear go-to-market strategy and meaningful revenue.
Key focus areas include Implement training loops, curate datasets, and drive high-priority experiments, Partner with cross-functional teams to close feedback loops from edge cases, and Collaborate on model development using PyTorch.
Important skills include PyTorch, Transformer Building Blocks, LLM Building Blocks, ViT, DETR, and Mask2Former. Preferred (not required): FastAPI, Flask, Docker, and Amazon S3.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About Kinetic Kinetic Automation is building a network of automated repair centers for modern vehicles. The auto industry is transitioning from mechanically complex vehicles to mechanically simple ones with complex software and technology. Kinetic aims to be the primary infrastructure-as-a-service for servicing future vehicles with our robotic repair centers, powered by our proprietary software and AI. We are a strong team of experienced robotics + automotive + shared mobility enthusiasts who have worked in self-driving, mapping, lidar, motorsport, and ride-sharing. We are a venture backed startup (Series B) with a clear go-to-market strategy and meaningful revenue.
About the role You will be a part of a small, production-minded ML team based in Orange County/Oakland. You’ll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data.
Experience & Skills Required
- Deep ML / CV Fundamentals: You need hands-on experience training and evaluating deep models for segmentation and detection (PyTorch). You must understand how Transformer/LLM building blocks map to vision (ViT/DETR/Mask2Former) and have practical exposure to 2D/3D data, point clouds, and camera geometry
- Curiosity & Strict Attention to Detail: You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate trade-offs
- AI-Empowered, Not AI-Dependent: We strongly encourage leveraging AI tools (Copilot, ChatGPT, Claude) to maximize your efficiency. However, you must 100% understand the underlying details of the code you ship. We are looking for strong independent thinkers and debuggers, not someone who simply passes along AI outputs without deep comprehension
- Working knowledge of transformer and LLM building blocks applied to vision, including self-attention, positional encodings, tokenization, and mapping these ideas to vision models (e.g., ViT, DETR, Mask2Former)
- Practical exposure to 3D/depth data, including familiarity with point clouds, camera geometry (intrinsics/extrinsics), basic calibration, and multi-view geometry
- Proficiency in Python and the relevant tech stack: PyTorch, torchvision, Detectron2 or MMDetection/Segmentation, and Hugging Face Transformers
- Experience with Python services (FastAPI/Flask), Docker, and AWS services (S3, Batch/EC2, ECR) is preferred.
- Strong communication skills with the ability to write tidy PRs, experiment logs, and short design notes to ensure reproducibility Responsibilities
- The Work: Implement training loops, curate datasets, drive high-priority experiments, and partner with cross-functional teams to close feedback loops from edge cases
- The Stack: PyTorch, Detectron2 / MMDetection / Segmentation, Hugging Face Transformers, Python (FastAPI), Docker, AWS
- Collaborate on model development by implementing training loops, losses, augmentations, and evaluations using PyTorch
- Keep current with the industry by summarizing relevant papers and PRs, and proposing small, testable improvements
- Contribute to datasets by helping define labeling guidelines, curating splits, running quality checks, and maintaining data versioning
- Run experiments to track metrics, perform ablations, write clear experiment notes, and present findings.
- Provide production support by exporting models, writing basic inference code, adding tests, and assisting with performance profiling
- Work cross-functionally, partnering with backend engineers on APIs, containers, and CI, and with ops/labeling teams on edge cases and feedback loops Benefits
- Competitive salary and equity package
- Comprehensive health and dental insurance
- Retirement savings plan.
- Paid time off and holidays
Kinetic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, military status, or any protected attribute. We encourage qualified candidates from all backgrounds to apply and join us in our mission. If you require accommodation at any stage of the application process due to a disability, please let us know.
How this job compares
Set against the 5,888 open Machine Learning Engineer jobs on Olive Jobs, counted October 27, 2026.
- Pay
- This postingNot listed
- California median$174–260K/yr1,326 salary ranges
- California median$35–78/hr29 hourly ranges
- Openings
- Olive Jobs lists 1,791 open Machine Learning Engineer jobs in California and 5,888 across the US. 5% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 6 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (4,725 postings).
- Education
- 2,412 of the 5,888 open Machine Learning Engineer jobs (41%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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